Multi-aspect Graph Contrastive Learning for Review-enhanced Recommendation

K Wang, Y Zhu, T Zang, C Wang, K Liu… - ACM Transactions on …, 2023 - dl.acm.org
Review-based recommender systems explore semantic aspects of users' preferences by
incorporating user-generated reviews into rating-based models. Recent works have …

Enhanced Hierarchical Contrastive Learning for Recommendation

K Wang, Y Zhu, T Zang, C Wang, M Jing - Proceedings of the AAAI …, 2024 - ojs.aaai.org
Designed to establish potential relations and distill high-order representations, graph-based
recommendation systems continue to reveal promising results by jointly modeling ratings …

Multi-Channel Hypergraph Contrastive Learning for Matrix Completion

X Li, C Shui, Y Yu, C Huang, Z Zhao, J Dong - arXiv preprint arXiv …, 2024 - arxiv.org
Rating is a typical user explicit feedback that visually reflects how much a user likes a
related item. The (rating) matrix completion is essentially a rating prediction process, which …

Hierarchical Graph Contrastive Learning for Review-Enhanced Recommendation

C Shui, X Li, J Qi, G Jiang, Y Yu - Joint European Conference on Machine …, 2024 - Springer
In comparison to numerical ratings and implicit feedback, textual reviews offer a deeper
understanding of user preferences and item attributes. Recent research underscores the …

ICCVAE: Item Concept Causal Variational Auto-Encoder for top-n recommendation

J Feng, Q Wang, Z Huang… - 2023 8th International …, 2023 - ieeexplore.ieee.org
Recently, recommendation systems, especially interpretable ones, have become
increasingly popular. The recommendation system provides personalized recommendations …